The EQ Behind the IQ - Jaco Rossouw
•
1 like•626 views
This document discusses the growing disconnect between data-driven businesses and their customers due to a lack of understanding of human behavior and emotions. It recommends that companies understand their customer data, consider human behavior at key touchpoints, capture behavioral data, look for patterns, and experiment to improve the customer experience. While machines are valuable, the document also emphasizes not underestimating the power of human interactions and emotions (EQ) in business.
Report
Share
Report
Share
Download to read offline
Recommended
Thrusting - Tincup - Webinar
The document discusses how technology is thrusting HR into a leadership role and outlines expectations that are changing for HR departments. It notes that HR data needs to be connected both internally and externally. It also discusses how processes need to be agile and flexible, reporting needs to be easily accessible. It highlights that software needs to provide predictive insights and that HR needs to hire people with different skills like data analysis and coding. Finally, it mentions how work is shifting to accessing talent on an as-needed basis through freelancing and offsite work.
How to think like a data scientist
Data scientists look at data differently than normal people by focusing on opportunities in large datasets rather than just headlines. They turn data into information and insights. To think like a data scientist, start with a question about something that interests or bothers you, then identify relevant data sources to help answer your question. Companies should cultivate more data-focused managers since data skills are becoming important. Managers can use data analysis to improve processes, like determining why meetings often start late.
Why is AI so uncomfortable - A therapy session
Keynote from Wonderland AI Summit, focusing on why it is so hard to truly embrace AI for leaders, organizations and states. To go beyond using AI simply for a little extra efficiency, and actually dare to let AI give you new insights - which will require you to let go of the old way of doing things, and change.
Copy of getting into ai event slides (PDF)
1) The document discusses key principles of AI discussed at a conference: AI should enhance rather than replace humans, be transparent to build trust, and consider social impact.
2) Speakers addressed topics like the future of creativity, business, jobs, and education with AI, and that humans and computers together can better solve problems.
3) To be a data scientist requires skills like asking questions, experimenting, understanding failure, passion for a sector, and enjoying learning.
DEEP Scott Killoh-3
This document discusses how deep data can transform businesses, using media companies as an example. It notes that while traditional media companies are struggling, news consumption has actually increased in recent years. The growth is in digital formats among younger demographics. It suggests that with deep data, media companies can gain insights into customer behaviors and improve their digital products and services accordingly in real-time. This continuous refinement process could help revitalize media businesses.
AI For Healthcare : Doctors Augmentation
The document discusses how cognitive AI can augment doctors and clinicians by helping them address various challenges. It describes how doctors are challenged by the large volume of disparate data from various sources, keeping up with the constantly increasing research literature, selecting personalized treatment plans, and generating novel insights. Researchers face challenges such as exploring connections across domains and generating new insights. The document then introduces IBM Watson and describes how its capabilities such as natural language processing, machine learning, and visual recognition can help extract insights from vast amounts of data and published literature to help doctors understand patient conditions, formulate treatment options, and select personalized plans. It asserts that cognitive AI can engage patients, improve outcomes, and control costs in healthcare.
The First of Me! Insights from the Future of Digital at SxSW 2019
What does the title of a corny Hoobastank song have to do with SXSW 2019 takeaways? Absolutely everything. In this talk, we will explore the next frontier in personalisation—the trends, benefits and potential unintended consequences of Relevancy 2.0. Then we will focus on what organisations must do now to finally put the personal back into personalisation.
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
This is a panel/workshop session developed for NEXT 2014 in Berlin.
Guests:
Lisa Lang (Twilio) Anke Domscheit-Berg (Opengov.me) Olga Steidl (Linko ) Ivan P. Yamshchikov (Yandex) Felienne Hermans (TU Delft)
----
Content:
Everyone is talking about Big Data – but what’s really behind it and how can you make data work for your business?
Collecting data is just one part of the puzzle. To source the right information, read it so it makes sense and -finally- how to execute on it is the most important task for successful big data management.
At this panel workshop we’ll listen to a lot of examples from big companies who’re dealing with massive amount of data on a daily basis. Each panel member will give a short demo and insight to their strategies and might revile some surprising facts.
This workshop is organised in cooperation with Berlin Geekettes.
Recommended
Thrusting - Tincup - Webinar
The document discusses how technology is thrusting HR into a leadership role and outlines expectations that are changing for HR departments. It notes that HR data needs to be connected both internally and externally. It also discusses how processes need to be agile and flexible, reporting needs to be easily accessible. It highlights that software needs to provide predictive insights and that HR needs to hire people with different skills like data analysis and coding. Finally, it mentions how work is shifting to accessing talent on an as-needed basis through freelancing and offsite work.
How to think like a data scientist
Data scientists look at data differently than normal people by focusing on opportunities in large datasets rather than just headlines. They turn data into information and insights. To think like a data scientist, start with a question about something that interests or bothers you, then identify relevant data sources to help answer your question. Companies should cultivate more data-focused managers since data skills are becoming important. Managers can use data analysis to improve processes, like determining why meetings often start late.
Why is AI so uncomfortable - A therapy session
Keynote from Wonderland AI Summit, focusing on why it is so hard to truly embrace AI for leaders, organizations and states. To go beyond using AI simply for a little extra efficiency, and actually dare to let AI give you new insights - which will require you to let go of the old way of doing things, and change.
Copy of getting into ai event slides (PDF)
1) The document discusses key principles of AI discussed at a conference: AI should enhance rather than replace humans, be transparent to build trust, and consider social impact.
2) Speakers addressed topics like the future of creativity, business, jobs, and education with AI, and that humans and computers together can better solve problems.
3) To be a data scientist requires skills like asking questions, experimenting, understanding failure, passion for a sector, and enjoying learning.
DEEP Scott Killoh-3
This document discusses how deep data can transform businesses, using media companies as an example. It notes that while traditional media companies are struggling, news consumption has actually increased in recent years. The growth is in digital formats among younger demographics. It suggests that with deep data, media companies can gain insights into customer behaviors and improve their digital products and services accordingly in real-time. This continuous refinement process could help revitalize media businesses.
AI For Healthcare : Doctors Augmentation
The document discusses how cognitive AI can augment doctors and clinicians by helping them address various challenges. It describes how doctors are challenged by the large volume of disparate data from various sources, keeping up with the constantly increasing research literature, selecting personalized treatment plans, and generating novel insights. Researchers face challenges such as exploring connections across domains and generating new insights. The document then introduces IBM Watson and describes how its capabilities such as natural language processing, machine learning, and visual recognition can help extract insights from vast amounts of data and published literature to help doctors understand patient conditions, formulate treatment options, and select personalized plans. It asserts that cognitive AI can engage patients, improve outcomes, and control costs in healthcare.
The First of Me! Insights from the Future of Digital at SxSW 2019
What does the title of a corny Hoobastank song have to do with SXSW 2019 takeaways? Absolutely everything. In this talk, we will explore the next frontier in personalisation—the trends, benefits and potential unintended consequences of Relevancy 2.0. Then we will focus on what organisations must do now to finally put the personal back into personalisation.
BIG DATA MANAGEMENT - forget the hype, let's talk about the facts!
This is a panel/workshop session developed for NEXT 2014 in Berlin.
Guests:
Lisa Lang (Twilio) Anke Domscheit-Berg (Opengov.me) Olga Steidl (Linko ) Ivan P. Yamshchikov (Yandex) Felienne Hermans (TU Delft)
----
Content:
Everyone is talking about Big Data – but what’s really behind it and how can you make data work for your business?
Collecting data is just one part of the puzzle. To source the right information, read it so it makes sense and -finally- how to execute on it is the most important task for successful big data management.
At this panel workshop we’ll listen to a lot of examples from big companies who’re dealing with massive amount of data on a daily basis. Each panel member will give a short demo and insight to their strategies and might revile some surprising facts.
This workshop is organised in cooperation with Berlin Geekettes.
The field-guide-to-data-science
This document provides an introduction to data science. It defines data science as the art of turning data into actions through the creation of data products, which provide actionable information without exposing decision makers to underlying data or analytics. Data science differs from traditional analytics in its use of both deductive and inductive reasoning to discover new insights and test hypotheses. It also leverages interdisciplinary teams to generate prospective, actionable insights from diverse and real-time data sources. The goal of data science is to produce data products that answer key business questions and drive better decisions.
AI and the Future of Work [TUG-CO, 11/15/23]
This talk was given to the Tech User Group, Central Oregon on November 15th, 2023.
~~
AI revolutionizes the way we interact with information. It will change the way we work. In this talk, we will introduce the fundamental concepts and the latest research and policies in the field. We will then explore numerous opportunities and societal challenges related to technology adoption, work augmentation and identity. Finally, we will introduce Personal AI and the mission of Kwaai Lab.
Kwaai Lab, a non-profit, volunteer-based open-source AI lab, is composed of researchers, architects, developers, and philosophers. Our goal is to design and implement the tools, fundamentals, and policies that empower us all to own our own Personal AI assistants.
Salesforce - AI for CRM
Artificial intelligence (AI) is driven by advances in computing power, data storage, and algorithms. It will be more disruptive than previous technological shifts. AI techniques like machine learning, deep learning, and natural language processing are making platforms and systems smart enough to learn from data and interactions to anticipate needs and automate tasks. Consumers are already using AI without realizing it through apps from Google, Facebook, Amazon, and self-driving cars. This raises expectations for smart, seamless customer experiences from businesses. The e-book will explore how companies can take advantage of AI for sales, customer service, marketing, and other business functions.
AI for CRM e-book
Artificial intelligence (AI) is becoming a reality due to advances in three key areas: data models, data availability, and processing power. AI is present in many consumer apps through machine learning techniques. For businesses, AI can help address challenges around data silos, lack of data expertise, infrastructure constraints, and lack of context for AI. By connecting all customer data into a single view and using AI tools that anticipate needs, businesses can close the gap between intelligence and customer experience.
TCS Point of View Session - Analyze by Dr. Gautam Shroff, VP and Chief Scient...
TCS Point of View Session - Analyze by Dr. Gautam Shroff, VP and Chief Scient...Tata Consultancy Services
If insights are available from mass amounts of data, you require enormous agility across business units to act on these. Understand how your peers tackle such problems and what new approaches are available to businesses.The Field Guide to Data Science
Booz Allen's experts define the science and art of Data Science in the ground breaking The Field Guide to Data Science. The work unlocks the potential data provides in improving every aspect of our lives by explaining how to ask the right questions from data.
WHY DO SO MANY ANALYTICS PROJECTS STILL FAIL?
“KEY CONSIDERATIONS FOR DEEP ANALYTICS ON BIG DATA FOR DEEP LEARNING”
What is Big Data? Big Data, which means many things to many people, is not a new technological fad. In addition to providing innovative solutions and operational insights to enduring challenges and opportunuties, big data with deep analytics instigate new ways to transform processes, organizations, entire industries, and even society all together. Pushing the boundaries of deep data analytics uncovers new.
Big Data is not just “big.” The exponentially growing volume of the data is only one of many characteristics that are often associated with Big Data, such as variety, velocity, veracity and others (6Vs).
By now, we should already have knowledge and experience to have successful data and analytics enabled decision support systems. So why do these projects still fail, and why are executives and users are still so unhappy? While there are many reasons for this high failure rate, the biggest is that companies still treat these projects as just another IT project. Big data analytics is neither a product nor a computer system. It is, rather, a constantly evolving strategy, vision and architecture that continuously seek to align an organization’s operations and direction with its strategic business goals with strategic, tactical and operational decisions.
Why analytics projects fail
This document provides a summary of the July/August 2014 issue of the magazine Analytics. The summary includes:
- Key articles in the issue discuss real-time text analytics using social media data, why analytics projects fail, the bright job prospects for data scientists, how IBM has used analytics for transformation, and forecasts of popular analytics software.
- Short descriptions and headlines are provided for additional sections and departments in the magazine including executive interviews, columns on healthcare and other analytics topics, and previews of upcoming analytics conferences.
- Information is given about the magazine's publisher and editorial board. The magazine is published by INFORMS to support the analytics profession and drive better business decisions.
"Understanding Humans with Machines" (Arthur Tisi)
At NYAI #16, Arthur Tisi explores deep neural networks that dominate advanced approaches to pattern recognition. Today neural networks transcribe our speech, recognize our pets, understand linguistics and fight our trolls. Recent advances by Geoff Hinton and the introduction of capsule networks only ups the ante. But despite the results, we have to wonder… why do they work so well?
In this session, Arthur Tisi, CEO and Founder of MeaningBot, will share some extremely remarkable results in applying deep neural networks to natural language processing (NLP), particularly in the areas of determining human traits in the areas of leadership, team building, personality, consumption preferences and more. Arthur will cite real world examples and share some of the math and science behind these advances including different variants of artificial neural networks, such as deep multilayer perceptron (MLP), convolutional neural network (CNN), recursive neural network (RNN), recurrent neural network (RNN), long short-term memory (LSTM), sequence-to-sequence model, and shallow neural networks including word2vec for word embeddings.
Top 10 data science takeaways for executives
This document discusses data science and provides examples of how major companies are using it. It begins with definitions of data science and what data scientists do, involving skills in computer science, mathematics, statistics, programming, and telling stories from data. It then gives several examples of how large companies like Kroger, UPS, and American Express are using data science for applications like customer loyalty analysis, fleet optimization, and churn prediction to improve business outcomes. The document advocates that executives should understand data science and how leading companies are applying it in areas such as financial management, customer service, fraud detection, and revenue growth.
The Field Guide to Data Science
Data Science is the competitive advantage of the future for organizations interested in turning their data into a product through analytics. Industries from health, to national security, to finance, to energy can be improved by creating better data analytics through Data Science. The winners and the losers in the emerging data economy are going to be determined by their Data Science teams.
[REPORT PREVIEW] The AI Maturity Playbook: Five Pillars of Enterprise Success
[REPORT PREVIEW] The AI Maturity Playbook: Five Pillars of Enterprise SuccessAltimeter, a Prophet Company
This document presents a maturity model for artificial intelligence adoption in enterprises. It outlines four stages of maturity: exploring, experimenting, formalizing, and integrating. It also discusses four macro trends affecting AI success: the shift from screen-based to sensory interactions; from rules-based to probabilistic decision making; from data analytics to data engineering; and from expertise-driven to data-driven leadership. Key aspects of maturity include having a data strategy, using AI in product development, establishing ethics principles, and integrating AI throughout the organization.Onboarding AI by Jana Eggers
Globant and the California College of the Arts (CCA) got together to present CON.VERGE, their first conference for business executives and thought-leaders.
Jana Eggers leads a neuroscience-based artificial intelligence company focused on turning big data into smart actions. Her tech experience comes from positions at Intuit, Blackbaud, Lycos, American Airline’s Sabre, and Spreadshirt. She is a mathematician with a computer science.
During her talk during the event, Digital Disrupters - Visionary Thinking, she elaborated on how Artificial Intelligence offers a new approach on how we analyze the data. Check out her presentation for more details.
Getting into ai event slides
This document provides an overview of a community and directory for all things related to artificial intelligence. It summarizes discussions from various speakers on topics like the future of AI, how AI will impact jobs and business, creativity and art, ethics and privacy, and career opportunities in AI. The document also provides advice on how to prepare for a career in AI through attending events, learning from newsletters and podcasts, getting experience, and networking with people working in the field.
What Will Our Future Be In The World Of Artificial Intelligence
The new center at Cambridge University explores the exciting possibilities and dangers of rapidly evolving AI while also challenging your preconceptions about what AI is.
What is data science? No really, what is a data scientist?
This presentation was adapted from content and spired by by Eva-Marie Muller-Stuler, my friend and fellow IBMer. Learn the secret sauce of becoming a data scientist, including the soft & hard skills necessary to be successful in your data science career journey.
Why the ‘Old Brain’ Struggles with Big Data - Deloitte CIO - WSJ
This article discusses how people's fears about big data may stem from their "old brain" instincts rather than rational thinking. It argues that while big data collection raises valid privacy concerns, the technology also has great potential to improve lives if used appropriately. The article urges focusing on positive applications and ensuring data is only used for beneficial purposes, rather than opposing big data due to hypothetical fears.
Human, AI collaboration, Accenture
Great report from Accenture. AI and ML are shaping human capabilities to ensure a better human/machine collaboration. This is how CEOs and CIOs should look at talent to take fully advantage of the new technologies.
2009 06 few
This document discusses the importance of data visualization and analysis. It contains summaries of research and ideas from experts in the field like Stephen Few, Colin Ware, Edward Tufte, and others. The key points are:
- Data visualization can help make sense of information and reveal patterns and insights that are difficult to see in raw data. It allows humans to leverage their highly visual perception abilities.
- Most organizations are not effectively analyzing the data they already have access to in order to improve business outcomes. Simple visualization techniques can help make meaningful insights more accessible.
- While technology has increased access to data, the focus needs to shift to understanding and communicating important and actionable insights from the data through visualization.
Democratizing Intelligence - Sri Ambati, CEO & Co-Founder, H2O.ai
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/ZrlJQqNaSMI.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://www.twitter.com/h2oai.
Organizational Change Leadership Agile Tour Geneve 2024
Organizational Change Leadership at Agile Tour Geneve 2024
More Related Content
Similar to The EQ Behind the IQ - Jaco Rossouw
The field-guide-to-data-science
This document provides an introduction to data science. It defines data science as the art of turning data into actions through the creation of data products, which provide actionable information without exposing decision makers to underlying data or analytics. Data science differs from traditional analytics in its use of both deductive and inductive reasoning to discover new insights and test hypotheses. It also leverages interdisciplinary teams to generate prospective, actionable insights from diverse and real-time data sources. The goal of data science is to produce data products that answer key business questions and drive better decisions.
AI and the Future of Work [TUG-CO, 11/15/23]
This talk was given to the Tech User Group, Central Oregon on November 15th, 2023.
~~
AI revolutionizes the way we interact with information. It will change the way we work. In this talk, we will introduce the fundamental concepts and the latest research and policies in the field. We will then explore numerous opportunities and societal challenges related to technology adoption, work augmentation and identity. Finally, we will introduce Personal AI and the mission of Kwaai Lab.
Kwaai Lab, a non-profit, volunteer-based open-source AI lab, is composed of researchers, architects, developers, and philosophers. Our goal is to design and implement the tools, fundamentals, and policies that empower us all to own our own Personal AI assistants.
Salesforce - AI for CRM
Artificial intelligence (AI) is driven by advances in computing power, data storage, and algorithms. It will be more disruptive than previous technological shifts. AI techniques like machine learning, deep learning, and natural language processing are making platforms and systems smart enough to learn from data and interactions to anticipate needs and automate tasks. Consumers are already using AI without realizing it through apps from Google, Facebook, Amazon, and self-driving cars. This raises expectations for smart, seamless customer experiences from businesses. The e-book will explore how companies can take advantage of AI for sales, customer service, marketing, and other business functions.
AI for CRM e-book
Artificial intelligence (AI) is becoming a reality due to advances in three key areas: data models, data availability, and processing power. AI is present in many consumer apps through machine learning techniques. For businesses, AI can help address challenges around data silos, lack of data expertise, infrastructure constraints, and lack of context for AI. By connecting all customer data into a single view and using AI tools that anticipate needs, businesses can close the gap between intelligence and customer experience.
TCS Point of View Session - Analyze by Dr. Gautam Shroff, VP and Chief Scient...
TCS Point of View Session - Analyze by Dr. Gautam Shroff, VP and Chief Scient...Tata Consultancy Services
If insights are available from mass amounts of data, you require enormous agility across business units to act on these. Understand how your peers tackle such problems and what new approaches are available to businesses.The Field Guide to Data Science
Booz Allen's experts define the science and art of Data Science in the ground breaking The Field Guide to Data Science. The work unlocks the potential data provides in improving every aspect of our lives by explaining how to ask the right questions from data.
WHY DO SO MANY ANALYTICS PROJECTS STILL FAIL?
“KEY CONSIDERATIONS FOR DEEP ANALYTICS ON BIG DATA FOR DEEP LEARNING”
What is Big Data? Big Data, which means many things to many people, is not a new technological fad. In addition to providing innovative solutions and operational insights to enduring challenges and opportunuties, big data with deep analytics instigate new ways to transform processes, organizations, entire industries, and even society all together. Pushing the boundaries of deep data analytics uncovers new.
Big Data is not just “big.” The exponentially growing volume of the data is only one of many characteristics that are often associated with Big Data, such as variety, velocity, veracity and others (6Vs).
By now, we should already have knowledge and experience to have successful data and analytics enabled decision support systems. So why do these projects still fail, and why are executives and users are still so unhappy? While there are many reasons for this high failure rate, the biggest is that companies still treat these projects as just another IT project. Big data analytics is neither a product nor a computer system. It is, rather, a constantly evolving strategy, vision and architecture that continuously seek to align an organization’s operations and direction with its strategic business goals with strategic, tactical and operational decisions.
Why analytics projects fail
This document provides a summary of the July/August 2014 issue of the magazine Analytics. The summary includes:
- Key articles in the issue discuss real-time text analytics using social media data, why analytics projects fail, the bright job prospects for data scientists, how IBM has used analytics for transformation, and forecasts of popular analytics software.
- Short descriptions and headlines are provided for additional sections and departments in the magazine including executive interviews, columns on healthcare and other analytics topics, and previews of upcoming analytics conferences.
- Information is given about the magazine's publisher and editorial board. The magazine is published by INFORMS to support the analytics profession and drive better business decisions.
"Understanding Humans with Machines" (Arthur Tisi)
At NYAI #16, Arthur Tisi explores deep neural networks that dominate advanced approaches to pattern recognition. Today neural networks transcribe our speech, recognize our pets, understand linguistics and fight our trolls. Recent advances by Geoff Hinton and the introduction of capsule networks only ups the ante. But despite the results, we have to wonder… why do they work so well?
In this session, Arthur Tisi, CEO and Founder of MeaningBot, will share some extremely remarkable results in applying deep neural networks to natural language processing (NLP), particularly in the areas of determining human traits in the areas of leadership, team building, personality, consumption preferences and more. Arthur will cite real world examples and share some of the math and science behind these advances including different variants of artificial neural networks, such as deep multilayer perceptron (MLP), convolutional neural network (CNN), recursive neural network (RNN), recurrent neural network (RNN), long short-term memory (LSTM), sequence-to-sequence model, and shallow neural networks including word2vec for word embeddings.
Top 10 data science takeaways for executives
This document discusses data science and provides examples of how major companies are using it. It begins with definitions of data science and what data scientists do, involving skills in computer science, mathematics, statistics, programming, and telling stories from data. It then gives several examples of how large companies like Kroger, UPS, and American Express are using data science for applications like customer loyalty analysis, fleet optimization, and churn prediction to improve business outcomes. The document advocates that executives should understand data science and how leading companies are applying it in areas such as financial management, customer service, fraud detection, and revenue growth.
The Field Guide to Data Science
Data Science is the competitive advantage of the future for organizations interested in turning their data into a product through analytics. Industries from health, to national security, to finance, to energy can be improved by creating better data analytics through Data Science. The winners and the losers in the emerging data economy are going to be determined by their Data Science teams.
[REPORT PREVIEW] The AI Maturity Playbook: Five Pillars of Enterprise Success
[REPORT PREVIEW] The AI Maturity Playbook: Five Pillars of Enterprise SuccessAltimeter, a Prophet Company
This document presents a maturity model for artificial intelligence adoption in enterprises. It outlines four stages of maturity: exploring, experimenting, formalizing, and integrating. It also discusses four macro trends affecting AI success: the shift from screen-based to sensory interactions; from rules-based to probabilistic decision making; from data analytics to data engineering; and from expertise-driven to data-driven leadership. Key aspects of maturity include having a data strategy, using AI in product development, establishing ethics principles, and integrating AI throughout the organization.Onboarding AI by Jana Eggers
Globant and the California College of the Arts (CCA) got together to present CON.VERGE, their first conference for business executives and thought-leaders.
Jana Eggers leads a neuroscience-based artificial intelligence company focused on turning big data into smart actions. Her tech experience comes from positions at Intuit, Blackbaud, Lycos, American Airline’s Sabre, and Spreadshirt. She is a mathematician with a computer science.
During her talk during the event, Digital Disrupters - Visionary Thinking, she elaborated on how Artificial Intelligence offers a new approach on how we analyze the data. Check out her presentation for more details.
Getting into ai event slides
This document provides an overview of a community and directory for all things related to artificial intelligence. It summarizes discussions from various speakers on topics like the future of AI, how AI will impact jobs and business, creativity and art, ethics and privacy, and career opportunities in AI. The document also provides advice on how to prepare for a career in AI through attending events, learning from newsletters and podcasts, getting experience, and networking with people working in the field.
What Will Our Future Be In The World Of Artificial Intelligence
The new center at Cambridge University explores the exciting possibilities and dangers of rapidly evolving AI while also challenging your preconceptions about what AI is.
What is data science? No really, what is a data scientist?
This presentation was adapted from content and spired by by Eva-Marie Muller-Stuler, my friend and fellow IBMer. Learn the secret sauce of becoming a data scientist, including the soft & hard skills necessary to be successful in your data science career journey.
Why the ‘Old Brain’ Struggles with Big Data - Deloitte CIO - WSJ
This article discusses how people's fears about big data may stem from their "old brain" instincts rather than rational thinking. It argues that while big data collection raises valid privacy concerns, the technology also has great potential to improve lives if used appropriately. The article urges focusing on positive applications and ensuring data is only used for beneficial purposes, rather than opposing big data due to hypothetical fears.
Human, AI collaboration, Accenture
Great report from Accenture. AI and ML are shaping human capabilities to ensure a better human/machine collaboration. This is how CEOs and CIOs should look at talent to take fully advantage of the new technologies.
2009 06 few
This document discusses the importance of data visualization and analysis. It contains summaries of research and ideas from experts in the field like Stephen Few, Colin Ware, Edward Tufte, and others. The key points are:
- Data visualization can help make sense of information and reveal patterns and insights that are difficult to see in raw data. It allows humans to leverage their highly visual perception abilities.
- Most organizations are not effectively analyzing the data they already have access to in order to improve business outcomes. Simple visualization techniques can help make meaningful insights more accessible.
- While technology has increased access to data, the focus needs to shift to understanding and communicating important and actionable insights from the data through visualization.
Democratizing Intelligence - Sri Ambati, CEO & Co-Founder, H2O.ai
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/ZrlJQqNaSMI.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://www.twitter.com/h2oai.
Similar to The EQ Behind the IQ - Jaco Rossouw (20)
TCS Point of View Session - Analyze by Dr. Gautam Shroff, VP and Chief Scient...
TCS Point of View Session - Analyze by Dr. Gautam Shroff, VP and Chief Scient...
"Understanding Humans with Machines" (Arthur Tisi)
"Understanding Humans with Machines" (Arthur Tisi)
[REPORT PREVIEW] The AI Maturity Playbook: Five Pillars of Enterprise Success
[REPORT PREVIEW] The AI Maturity Playbook: Five Pillars of Enterprise Success
What Will Our Future Be In The World Of Artificial Intelligence
What Will Our Future Be In The World Of Artificial Intelligence
What is data science? No really, what is a data scientist?
What is data science? No really, what is a data scientist?
Why the ‘Old Brain’ Struggles with Big Data - Deloitte CIO - WSJ
Why the ‘Old Brain’ Struggles with Big Data - Deloitte CIO - WSJ
Democratizing Intelligence - Sri Ambati, CEO & Co-Founder, H2O.ai
Democratizing Intelligence - Sri Ambati, CEO & Co-Founder, H2O.ai
Recently uploaded
Organizational Change Leadership Agile Tour Geneve 2024
Organizational Change Leadership at Agile Tour Geneve 2024
Recruiting in the Digital Age: A Social Media Masterclass
In this masterclass, presented at the Global HR Summit on 5th June 2024, Luan Wise explored the essential features of social media platforms that support talent acquisition, including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok.
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
In the Adani-Hindenburg case, what is SEBI investigating.pptx
Adani SEBI investigation revealed that the latter had sought information from five foreign jurisdictions concerning the holdings of the firm’s foreign portfolio investors (FPIs) in relation to the alleged violations of the MPS Regulations. Nevertheless, the economic interest of the twelve FPIs based in tax haven jurisdictions still needs to be determined. The Adani Group firms classed these FPIs as public shareholders. According to Hindenburg, FPIs were used to get around regulatory standards.
Digital Transformation and IT Strategy Toolkit and Templates
This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
Editable Toolkit to help you reuse our content: 700 Powerpoint slides | 35 Excel sheets | 84 minutes of Video training
This PowerPoint presentation is only a small preview of our Toolkits. For more details, visit www.domontconsulting.com
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...
Dive into the steadfast world of the Taurus Zodiac Sign. Discover the grounded, stable, and logical nature of Taurus individuals, and explore their key personality traits, important dates, and horoscope insights. Learn how the determination and patience of the Taurus sign make them the rock-steady achievers and anchors of the zodiac.
Creative Web Design Company in Singapore
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
LA HUG - Video Testimonials with Chynna Morgan - June 2024
Have you ever heard that user-generated content or video testimonials can take your brand to the next level? We will explore how you can effectively use video testimonials to leverage and boost your sales, content strategy, and increase your CRM data.🤯
We will dig deeper into:
1. How to capture video testimonials that convert from your audience 🎥
2. How to leverage your testimonials to boost your sales 💲
3. How you can capture more CRM data to understand your audience better through video testimonials. 📊
Best practices for project execution and delivery
A select set of project management best practices to keep your project on-track, on-cost and aligned to scope. Many firms have don't have the necessary skills, diligence, methods and oversight of their projects; this leads to slippage, higher costs and longer timeframes. Often firms have a history of projects that simply failed to move the needle. These best practices will help your firm avoid these pitfalls but they require fortitude to apply.
Satta Matka Dpboss Matka Guessing Kalyan Chart Indian Matka Kalyan panel Chart
Satta Matka Dpboss Matka Guessing Kalyan Chart Indian Matka Kalyan panel Chart➒➌➎➏➑➐➋➑➐➐Dpboss Matka Guessing Satta Matka Kalyan Chart Indian Matka
SATTA MATKA SATTA FAST RESULT KALYAN TOP MATKA RESULT KALYAN SATTA MATKA FAST RESULT MILAN RATAN RAJDHANI MAIN BAZAR MATKA FAST TIPS RESULT MATKA CHART JODI CHART PANEL CHART FREE FIX GAME SATTAMATKA ! MATKA MOBI SATTA 143 spboss.in TOP NO1 RESULT FULL RATE MATKA ONLINE GAME PLAY BY APP SPBOSSBuilding Your Employer Brand with Social Media
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
Part 2 Deep Dive: Navigating the 2024 Slowdown
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
Exploring Patterns of Connection with Social Dreaming
Exploring Patterns of Connection -Introduction to Social Dreaming
#Systems Psychodynamics
#Innovation
#Creativity
#Consultancy
#Coaching
-- June 2024 is National Volunteer Month --
Check out our June display of books on voluntary organisations
Recently uploaded (20)
Organizational Change Leadership Agile Tour Geneve 2024
Organizational Change Leadership Agile Tour Geneve 2024
Recruiting in the Digital Age: A Social Media Masterclass
Recruiting in the Digital Age: A Social Media Masterclass
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
ModelingMarketingStrategiesMKS.CollumbiaUniversitypdf
The Influence of Marketing Strategy and Market Competition on Business Perfor...
The Influence of Marketing Strategy and Market Competition on Business Perfor...
In the Adani-Hindenburg case, what is SEBI investigating.pptx
In the Adani-Hindenburg case, what is SEBI investigating.pptx
Digital Transformation and IT Strategy Toolkit and Templates
Digital Transformation and IT Strategy Toolkit and Templates
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...
LA HUG - Video Testimonials with Chynna Morgan - June 2024
LA HUG - Video Testimonials with Chynna Morgan - June 2024
Satta Matka Dpboss Matka Guessing Kalyan Chart Indian Matka Kalyan panel Chart
Satta Matka Dpboss Matka Guessing Kalyan Chart Indian Matka Kalyan panel Chart
Exploring Patterns of Connection with Social Dreaming
Exploring Patterns of Connection with Social Dreaming
The EQ Behind the IQ - Jaco Rossouw
- 1. The EQ Behind IQ The growing disconnect between “data-driven” businesses & their customers.
- 2. A sonnet written by a machine will be better appreciated by another machine. Alan Turning The father of AI
- 3. Why am I talking about machines & EQ? Jaco Rossouw CEO of Principa, an international data analytics and software company.
- 4. The one thing we all have in common
- 5. A tale of two customer service experiences
- 6. We are drowning in information, but starving for wisdom. E.O Wilson Biologist, Theorist & Naturalist
- 7. So, where’s the opportunity
- 8. Mind the gap
- 11. How do you make this happen 1 Understand your current data universe 2 Think about human behaviour at key touchpoints 3 Capture as much behavioural information as possible 4 Look for patterns and correlations 5 Experiment (deploy, test, refine)
- 12. In the age of machines, don’t underestimate the power and value of a human.
- 13. CAPE TOWN HEAD OFFICE Northgate Park, Platinum Dr Paarden Eiland 7405 +27 21 680 6000 www.principa.co.za JOHANNESBURG SALES OFFICE 342 Jan Smuts Ave Hyde Park 2196 +27 11 560 6950 insights.principa.co.za